Systems and method for medical platform employing artificial intellegence and wearable devices

ABSTRACT

A system, method and computer program product for a medical platform, including a wearable device configured to collect implicit patient information; a database configured to receive the implicit and explicit patient information from the wearable device and generate aggregated patient information; a machine learning system configured to receive the aggregated patient information from the database and generate personalized patient intervention information; and a patient user interface configured to receive patient intervention information.

CROSS REFERENCE TO RELATED DOCUMENTS

The present invention claims priority to U.S. Provisional PatentApplication Ser. No. 62/550,364 of Behjat IRANPOUR MOBARAKEH, entitled“MEDICAL PLATFORM,” filed on 25 Aug. 2017, the entire disclosure ofwhich is hereby incorporated by reference herein.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention generally relates to systems and methods formedical platforms, and more particularly to a method, system andcomputer program product for a medical platform employing artificialintelligence and wearable devices, and the like.

Discussion of the Background

Interconnection of diseases and their effect on human physical, mentaland behavioral health is a complex matter that results in a complextreatment with multiple factors in management thereof. There is a hugedemand for personalized early intervention and treatment. Despite theadvances in genetics and the understanding of the genetic influences onhuman behavior and hereditary diseases, we know little about non-geneticinfluences, known collectively as the personal environment, for example,including climate, social and economic settings related to the person,on overall person's physical, mental, and behavioral health, and thelike. Furthermore, current systems and methods fail to measureobjectively, for example, emotional and physical responses of a person,such as pain, mood, and the like, to external stressors, includingeconomic, social, climate factors, and the like.

There has been revolutionary advancement in machine learning methods,artificial intelligent computing, voice recognition and communicationtechnologies in the last 20 years. Such technological advancements havechanged the way humans communicate with each other, particularly,millennial and younger generations. Communicating over voice withintelligent robots and text messaging and using social networkingplatform to discuss health related issues with doctors, healthprofessionals, care givers and care providers are common. Many careproviders use care delivery using such systems. In addition, there is agap in connecting and mining such data sets and empowering and enablingpatients with tools, and the like, so they can participate in designinga most effective and personalized treatment, and the like. However, theinvention and embodiments described herein, have not been addressed orpresented in any prior art.

SUMMARY OF THE INVENTION

Therefore, there is a need for a method and system that addresses theabove and other problems. The above and other problems are addressed bythe illustrative embodiments of the present invention, which provide inillustrative embodiments, for example, a method, system and computerprogram product for a medical platform employing artificial intelligenceand wearable devices, and the like, including a social network, asecurity module, a privacy module, and the like, advantageously,employed for treatment, prevention, and the like, with a feedbackmodule, to improve system performance, and the like.

Accordingly, in illustrative aspects of the present invention there isprovided a system for ***BASED ON FINAL CLAIMS

Still other aspects, features, and advantages of the present inventionare readily apparent from the following detailed description, byillustrating a number of illustrative embodiments and implementations,including the best mode contemplated for carrying out the presentinvention. The present invention is also capable of other and differentembodiments, and its several details can be modified in variousrespects, all without departing from the spirit and scope of the presentinvention. Accordingly, the drawings and descriptions are to be regardedas illustrative in nature, and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments of the present invention are illustrated by way ofexample, and not by way of limitation, in the figures of theaccompanying drawings and in which like reference numerals refer tosimilar elements and in which:

FIG. 1 is used to illustrate components and factors that effect apatient's health and treatment result;

FIG. 2 is used to illustrate high comorbidity among various disease;

FIG. 3 is used to illustrate effect of social support on behavioraltherapy;

FIG. 4 is used to illustrate effect of smoking addiction on pregnantwoman and her baby;

FIG. 5 is used to illustrate factors contributing to chronic conditions;

FIG. 6 is used to illustrate a system and method for a patient centric,collaborative, chronic condition engagement and management platform;

FIG. 7 is used to illustrate a comprehensive patient remote monitoringdashboard for a researcher and a care provider;

FIG. 8 is used to illustrate a Patient Controlled Health ECO-system (PCHECO-system) infrastructure;

FIG. 9 is used to illustrate a voice enable personal assistant of thePCH ECU-system;

FIG. 10 is used to illustrate a technology infrastructure;

FIG. 11 is used to illustrate functioning objectives in design anddevelopment of components within the PCH ECO-system;

FIG. 12 is used to illustrate a set of features, advantageous, for abetter health outcome;

FIG. 13 is used to illustrate the PCH ECO-system integration within ahospital system;

FIG. 14 is used to illustrate the PCH ECO-system data flow;

FIG. 15 is used to illustrate market analysis with a focus on a new mom;

FIG. 16 is used to illustrate user expectations and behaviors with afocus on millennial parents;

FIG. 17 is used to illustrate a customized version of the PCH ECO-systemfor a new mom;

FIG. 18 is used to illustrate a two-tier service offering for a mom ofthe PCH ECU-system;

FIG. 19 is used to illustrate a general three-tier service offering ofthe PCH ECO-system;

FIG. 20 is used to illustrate a high-level architecture of the PCHECO-system;

FIG. 21 is used to illustrate features and components of the PCHECO-system;

FIG. 22 is used to illustrate a high-level data flow for a populating apopulation health system of the PCH ECO-system;

FIG. 23 is used to illustrate a high-level logical flow of sub-systemsinteractions within the PCH ECO-system; and

FIG. 24 is used to illustrate a high-level design system modules andengines of the PCH ECO-system and method.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

An illustrative system, method and computer program product for amedical platform employing artificial intelligence and wearable devices,and the like, are described. In the following description, for purposesof explanation, numerous specific details are set forth in order toprovide a thorough understanding of the present invention. It isapparent to one skilled in the science, however, that the presentinvention may be practiced without these specific details or with anequivalent arrangement or with one module deployed in the absence of theother. In some instances, well-known devices and structures are shown inblock diagram in order to avoid unnecessarily obscuring the presentinvention. The terminology used herein is for the purpose of describingparticular embodiments only and is not intended to be limiting of theinvention. As used herein, the term “and/or” includes any and allcombinations of one or more of the associated listed items. As usedherein, the singular forms “a,” “an,” and “the” are intended to includethe plural forms as well as the singular forms, unless the contextclearly indicates otherwise. It will be further understood that theterms “comprises” and/or “comprising,” when used in this specification,specify the presence of stated features, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, steps, operations, elements, components, and/orgroups thereof. Unless otherwise defined, all terms (including technicaland scientific terms) used herein have the same meaning as commonlyunderstood by one having ordinary skill in the art to which thisinvention belongs. It will be further understood that terms, such asthose defined in commonly used dictionaries, should be interpreted ashaving a meaning that is consistent with their meaning in the context ofthe relevant art and the present disclosure and will not be interpretedin an idealized or overly formal sense unless expressly so definedherein.

Referring now to the figures, wherein like reference numerals designateidentical or corresponding parts throughout the several views, and moreparticularly in FIGS. 1-24 thereof there is illustrated a method,system, and computer program product, for example, including a platform,for medical field to support effective treatment delivery system andresearch on mental and/or multi-chronic disease conditions, and thelike. Such a medical platform offers services that have been identifiedby researchers as advantageous for effective mental health andbehavioral therapy support system, for example, as shown in FIG. 1 thatis used to illustrate components and factors that effect a patient'shealth and treatment result, and the like.

Accordingly, in an illustrative embodiment, for example, a machinelearning engine (MLE) analyzes environmental information, publicrecords, user-provided feedback information (e.g., patient pin,individual bio sensor, brain wave data), collected information frombuilt-in private circle, support social networking system and built-inpublic forum, care-giver feedback data, individual clinical data, and/orgenomic and real time biomarker feedback data, and the like, to createfuzzy data sets that predict a potential human behavior and/or clinicaldiagnostic, which in turn provides a warning to the user and/orcaregiver (e.g., including individual who have legal permission toaccess these data) of a potential human behavior, deliveringpersonalized clinical and/or behavioral intervention and treatment, andthe like. The intervention and/or treatment can be delivered through amobile based interface and/or wearable device, and the like.

FIG. 2 is used to illustrate high comorbidity among various disease, andthe like. In FIG. 2 , displayed are the high comorbidity among deadlydiseases, for example, including Cancer, Depression and Smokingaddiction, and the like, with serious considerations (e.g., as furtherillustrated in FIG. 5 ), which call for a comprehensive diseasemanagement approach to discover the effect of interconnection of suchdiseases on human physical, mental and behavioral health, and the like,as well as the effect thereof on the results of a complex treatment withmultiple factors in managing of them individually or together. Socialsupport and continuum of care is an advantageous component that resultsin better treatment outcome for any suitable behavioral therapy.

Accordingly, FIG. 3 is used to illustrate effect of social support onbehavioral therapy. In FIG. 3 , how social support quadruple the successrate in a smoking cessation study in comparison with other methods isshown.

FIG. 4 is used to illustrate effect of smoking addiction on pregnantwoman and her baby. In FIG. 4 , for example, interdependency betweensmoking and post-partum depression (PPD) and other factors, and thelike, calls for a sophisticated design and treatment approach, and thelike. According, the illustrative Medical Platform of the presentinvention offers a multi-chronic condition, self-health-managementapplication built on artificial intelligent engine to further advancepatient support and research, and the like. Such a Medical Platform canbe based on open-architecture to ensure future scalability andflexibility. For Patients with Chronic conditions, there is provided avirtual place to track their treatment progress and collaborate withtheir care team for better outcome and referred to as PerSoN (e.g., asfurther illustrated in FIG. 6 ).

Accordingly, FIG. 5 illustrates factors contributing to chronicconditions, and the like, and FIG. 6 is used to illustrate a system andmethod for a patient centric, collaborative, chronic conditionengagement and management platform. In FIG. 6 , for example, a patientinterface 602 and care provider interface 601 are provided. Careprovider and researchers can remotely monitor patient reported outcomeand interact with patient within secure communication platform andprovide counseling service at any suitable time, location, and the like.

FIG. 7 is used to illustrate a comprehensive patient remote monitoringdashboard for a researcher and a care provider. In FIG. 7 , a Careprovider and Researchers interface 702 is provided, wherein the careprovider and/or researchers can view, for example, in real time, patientreported outcome 702 for different health modules relevant to a patient,for example, including smoking cessation 701, depression and chronicpain and symptoms modules, and the like.

FIG. 8 is used to illustrate a Patient Controlled Health ECO-system (PCHECO-system) infrastructure. FIG. 9 is used to illustrate a voice enablepersonal assistant of the PCH ECO-system. In FIGS. 8 and 9 , the PerSoNClinic components are configured, for example, as a distributedtechnology platform that can include any suitable hardware, devices, andthe like (e.g., Bio-Sensors, PerSoN Robotics, PerSoN pins, PerSoNTowers, Body Area Networks, Brainwave sensors, PCH ECO computerhardware), software (e.g., Machine Learning engine with fuzzy logicdatabase modeling, Artificial Intelligent engine, voice recognitionengine and voice enable communication module, data collection andtranslation engine, PerSoN's patient mobile Interface and care providerand researchers interface), and the like.

FIG. 10 is used to illustrate a technology infrastructure. In FIG. 10 ,a high level open architecture of PCH ECO-System can include, forexample, a Mobile Client cluster having Presentation layer 1001,Business layer 1002, Data Layer 1003 and Local Database 1004. Crosscutting-edge technologies for this cluster can include, for example,Security, Configuration and Communication/Connectivity protocols 1007,which communicate with a Mobile Support infrastructure layer, includingfor example, Services 1006 and Data Sources 1005.

FIG. 11 is used to illustrate functioning objectives in design anddevelopment of components within the PCH ECO-system. In FIG. 11 ,guiding principles in designing various features, for example, caninclude:

Inform; to provide patient with balanced and objective information toassist them in understanding their problem, alternatives, opportunitiesand/or behavior changes 1101.

Consult; to develop personalized treatments for patients based onpatient's real-time feedback 1102.

Empower; to provide an ultimate support system for patients andcaregivers on a daily basis 1104.

Collaborate; to partner with the patient and research communities toidentify the preferred solution to effect outcomes 1103.

FIG. 12 is used to illustrate a set of features, advantageous, for abetter health outcome. In FIG. 12 , PCH ECO-system preliminary freeservices to patient and their caregivers, for example, can includeenabling patient to set a clear and measurable treatment goal 1201,facilitating family and friends support for patient through virtualspace 1202, providing targeted and relevant education to patients andtheir support group 1203, enabling patients to monitor and track theirtreatment result 1204, and facilitating virtual mentoring and motivation1205. Advantageously, the PCH ECO-system open architecture and modulardesign provides flexibility and ease of integration into any suitablecare system. The PCH ECO-system novel machine learning engine 1706 canproduce such outcome based on the patient's record 2001 and the outputof Artificial Intelligent 2309 and personalized intervention engine2310.

FIG. 13 is used to illustrate the PCH ECO-system integration within ahospital system. In FIG. 13 , the PCH ECO-system functional modules canoperate independent of each other, wherein an Integrated EHR (ElectronicHealth Record) module 1301 can include HL7 and FHIR engine that enablesPCH ECO-System to integrate with any suitable EHR that complies with HL7and FHIR standards. In addition, the Integrated EHR module provides OpenAPI to give access to the patient's record. Both Open API and IntegratedHER required patient consent for accessing and/or retrieving patientrecords. Patient's Consent Signature can include Identifiers set bypatient for every patient's provided record within the PCH ECO-System.Such identifiers define what patient's record can be shared or not withwhom. A Connected Care module 1302 provides a communication hub betweenmultiple care provider who have access to patient record in PCHECO-system and can employ the Connected Care module for exchangingpatient information. A Patient Gateway 1303 facilitate comprehensivepatient interface and give patient access to their health recordhistory. Primary Care “E-Consult” 1304 and E-Health Coach 1307, E-Visit1308 modules can provide various levels of telehealth communications,and the like. A Patient Education 1305 module can provide patientrelevant education material based using patient health records and PCHECO-system machine learning engine (MLE)/Artificial Intelligence (AI)engine, and the like. The Multi Chronic Condition Management Program1306 allows patient access to various health modules, for example,including: Smoking cessation, Depression management, Chronic Pain andSymptom management, Food Diet management, Medication Management,Activity Management, and the like.

FIG. 14 is used to illustrate the PCH ECO-system data flow. In FIG. 14 ,the PCH ECO-system modular design with granular data collectionfacilitates bi-directional data flow for a better health outcome, andthe like.

FIG. 15 is used to illustrate market analysis with a focus on a new mom.FIG. 16 is used to illustrate user expectations and behaviors with afocus on millennial parents. In FIGS. 15-16 , specifications of thecurrent market with respect to millennial both as caregiver and as newparents and their unmet demand for comprehensive, affordable andconnected health care system is illustrated.

FIG. 17 is used to illustrate a customized version of the PCH ECO-systemfor a new mom. In FIG. 17 , a Grandma Clinic/Care module includes atechnology platform that addresses Postpartum depression 1704, new momisolation and smoking addiction 1701, among moms and expected moms.Real-time communication, such as WiFi technology, and the like, isprovided and advantageous for real-time measurements, for analysis ofthe totality of the situation, and the like. For example, with Grandmapins 1703 at/on mother's dress/body, as well as the infant's, a user canmonitor when and how long the baby was picked up or held by mother orbaby sitter, or violent shaking by an improper baby sitter can berecorded (and e.g., with alarm provided to suitable third parties), forexample, to prevent damages and monitor the health of a baby, as well asother studies to diagnose the problems with babies, through big dataanalysis, and the like. Such features can also be used correlate withthe bonding of baby with mother, with corresponding health consequences,and the like.

The pins 1703, for example, can be configured to be aestheticallypleasing for clothing or other suitable objects (e.g., purses), tomonitor events (e.g., holding a baby), to record data to analyze thedata later for health or safety reasons, and the like. The smart pinscan work in both directions, e.g., to measure biomarkers and tocommunicate to the system, or without biomarker, just measuring an event(e.g., holding a baby or a time period). For example, when a user startsfeeling pain, the user can measure the intensity using biosensors 1707,such as using chemicals, such as CO2 from the body for determining painlevel or stress level, and the like, and used to measure and analyze thecaptured data more accurately. Various biosensors or bio markers can beemployed, for example, for lung function or breathing. The PerSoN Pins1707 can include communication tags (e.g., Active and Passive), andwhich can include bio sensors based on NFC (near-field communication)enabled or simply an NFC tags (e.g., Active and Passive). Such tags areprogrammed to measure and track event driven specific factors related toa health condition, which then can trigger personalized warning and/orinitiate other module within the PerSoN Clinic health eco-system. Someapplications of PerSoN Pin are to measure health related events, such ashow long mom will hold the baby, how long an anxiety panic attack lasts,and the like. Event driven measurement of specific biomarker can beemployed, such as patient respiratory rate, when pain was rated (e.g.,at 9), and the like. For example, pain is very subjective measure andconcept, differing in various cultures and for various people. So, tomap that to the clinical definition, fuzzy logic can be employed, whichcan handle such types of measurements, concepts, and the like,algorithmically, mathematically, and her like. For example, behavior andpain could be modeled by fuzzy logic at 1706. The patient interacts andprovides feedback to the system through suitable applications and/orpersonal wearable devices and bio-sensors, and the like. A patientcommunication/interface module, includes patient's virtual circlesupport 1708 that can be a built on social networking platform, and thelike, and which can fully controlled by the patient, user, and the like.

This secure and private circle support social networking 1708 is one ofthe highly engaging modules within the system. The use of this modulefor patient participating in clinical trial can produce highly valuableimplicit data for patient with mental health issue. For example, thepatient can initiate and own such private virtual club and only patientcan invite support members to his/her private club. The members of suchprivate forum are for supporting the patient in their journeys to getbetter health. The system also provides training to support members onhow to provide effective support. Such training modules, for example,can include static, active and interactive modules, and the like.

The system can collect all suitable communications among club members,for example, including a level of member participation, and the like, insuch virtual club. Such data can produce valuable implicit data aboutpatient and care giver's behavior. The system can conduct detailedanalysis on member's words and conversation in such virtual club. Thepatient interface also provides access to a public forum withinpatient's mobile interface. Such forum is available to the public tojoin and participate in any suitable conversation. The system cancollect detailed information on the patient and patient support memberparticipation in such public forum.

FIG. 18 is used to illustrate a two-tier service offering for a mom ofthe PCH ECO-system. In FIG. 18 , various features of the PCH ECO-systemwithin patient and caregivers interface can be made available, forexample, free of charge through mobile application as Self Help at 1801.The Health Care and Health Coach 1802 provider version can be madeavailable, for example, as a Software as a Services (SaaS) to provide ahighly cost effective model.

FIG. 19 is used to illustrate a general three-tier service offering ofthe PCH ECO-system. In FIG. 19 , by employing an SaaS business model,the PCH ECO-system can provide a three tear product offering. Forexample, Researchers can use the PerSoN platform to collaborate withcaregivers and patients by combining patient clinical data,physiological, social behavior and environmental data with in VirtualClinical Trial environment. Care Providers can utilize the PerSoNplatform to monitor a patient's progress remotely and provideE-counseling and support services. Such level of participation can befee-based, intended for during and post-treatment monitoring. PatientSelf Help can be an evidence-based self-help support system, enablingpatients to log their symptoms, pain and depression utilizing NCIPRO-CTCAE symptom library and Depression management module. Such amodule can provide various levels of engagement to Inform, Consult,Collaborate and Empower the patient and caregiver. A free entry pointcan be employed to encourage enrollment, and the like.

FIG. 20 is used to illustrate a high-level architecture of the PCHECO-system. In FIG. 20 , the Patient controlled health eco-system (PCHECO System) can be commercialized as PerSoN (Personal Support Network)Clinic, as described below:

-   -   2001—PerSon Patient's Record: The database can include        individual record related to person from publicly available        databases, as well as propriety databases such as labs and        hospital records, including the following information: Person's        Clinical data; Person's Genetic data; Environmental data from        current and past person's locations; Person's civil and        criminal, financial and education records; Self-reported        person's life style and behavioral data, as well as collected        data from person's public record (e.g., shopping and reading        behavior, sports, traveling, and art interests); and Event        driven personal biomarker data, including bio sensor and        brainwave data, and the like.    -   2011—Population Health Database is aggregated collection of        publicly available health data and patients' record 2001. By        collecting public health data information and correlating with        the person's record, the machine learning engine can predict the        person's behaviors and assist the Intervention Engine to create        most effective intervention methods for the Person.    -   2012—The PerSoN patient interface as a mobile application and        related hardware devices can include PerSoN pin and PerSoN        Robotics. The PerSoN application is Mobile application that runs        on individual's (e.g., Patient and/or public user of PerSoN        application) phone and communicate with PerSoN hardware. Such        application can provide the following: Just on-time behavioral        intervention; Just on-time clinical intervention; Personal bio        sensor data collection; Personal health and life style input        data collection; Personalized and interactive health and life        style Educational module; Personalized behavioral and clinical        reporting; Personalized Virtual support community utilizing        latest social networking technology; Real time communication        with health and life style providers; and Real time, any time,        any place coaching, and the like.    -   1706—Machine Learning Engine: a suitable algorithm that collects        personal information from and combined them with public        information to create personalized predictive analysis and feeds        to precision intervention 2004.    -   2004—The core of Precision Behavioral and Clinical Intervention        Engine is an algorithm that uses aggregated patient data to        optimized Active data Modeling system over time and create        personalized behavioral and clinical intervention, based on        up-to-date collected, and provides just on time intervention        and/or treatment. This system uses latest evidenced based        treatment and intervention approaches and combines it with        patients' provided feedback to create personalized intervention.    -   2002 and 2003—Communication Layers: These modules facilitate        communication and data exchange between different internal and        external databases, health modules and biosensors and brainwave        sensors, wearable devices and PerSoN's NFC enabled bio sensors        and NFC pins.    -   2008—Patient uses Point of Care Touch box, which contains PerSoN        Clinic hardware and software solutions and wirelessly connects        local EMR and/or HER Database to patient's record by capturing        Patient ID (e.g., Patient Personal Biometrics ID or unique ID)        from patient through various means, including Contactless        connection and/or Patient touch.    -   2010 Patient communicates with PerSoN modules and system by        direct communication through PerSoN application (e.g., both        mobile and watch), PerSoN pins, wearable and/or sensor devices.    -   2001—PerSoN Pins are communication tags (e.g., Active and        Passive) which can be a bio sensor NFC (e.g., near-field        communication) enabled or simply an NFC tags (e.g., Active and        Passive). Such tags are programmed to measure and track event        driven specific factors related to a health condition, which        then can trigger personalized warning and/or initiate other        module within the PerSoN Clinic health eco-system. Some        applications of PerSoN Pin are to measure health related events,        such as: How long mom will hold the baby?; How long an anxiety        panic attack last?; Event driven measurement of specific        biomarker, for instance patient respiratory rate, when pain was        rated (e.g. at 9).

The specialty group is created, utilizing PCH ECO System technologyframework, to address specific health issue, for example, includingsubcomponents of the platform or system:

-   -   1—PerSoN Clinic (Personalized Support Network Clinic) is used as        multi-chronic condition management system. One of the versions        of this system focuses on managing three conditions: smoking        addiction, pain and depression. These conditions are highly        comorbid and system can produce most effective and personalized        intervention by engaging patient on daily basis.    -   2—Grandma Clinic/Care is the technology platform that addresses        Postpartum depression, new mom isolation and smoking addiction,        among moms and expected moms.    -   3—Rare Clinic: in this version, the patient with rare disease        volunteers to try a specific drug and provides her feedback for        better understanding of the disease and effectiveness of the        drug and/or treatment methods.    -   4—FDA Clinic: this is a patient-centric virtual FDA that        facilitates a global clinical trial for a specific drug.

Such systems can be configured as multi-lingual and available indifferent languages. The system and clinical/psychological solutions aredesigned to cure or prevent or diagnose or suggest a plan. So, they arebased on patient's background, and thus, they are culturally sensitive,based on e.g. ethnicity, language, sex, education, or prior experiences.They generate advantageous message or solution for intervention or cure.So, the patient/user has pure data or physical data getting separated ordistinguished from overall data, so that they can be analyzed separatelywith respect to other humans/prior data/experiences/history, for abetter diagnosis and cure. For example, pain is very subjective measureand concept, differing in various cultures and for various people. So,to map that to the clinical definition, we need fuzzy logic, which canhandle these kinds of measures/concepts mathematically. For example,behavior and pain would be modeled by fuzzy logic.

The Patient controlled health eco-system, is the multi-lingual Humancentered communication and support system for collecting human's relateddata and feedback, directly or indirectly, actively or passively,through patient interface and/or devices, to aggregate population healthdatabase with patient data including but not limited to clinical,genetic, life style, financial, social and civil behavioral datasetthrough distributed communication protocol within PCH ECO-system, to beused for Active Data Modeling and to train PCH ECO proprietary MachineLearning Engine and Artificial Intelligent Engines for providingbehavioral and clinical intervention notice in the form received by oneor multiple human senses (sight, hearing, smell, taste and touch). TheSystem provides private and public social networking, disease managementmodules, virtual community support and Virtual Charity Support. All thecomponents of the system are voice enable with interactive communicationthrough PerSoN Tower and other PerSoN proprietary devise and software.Wherein system provides researchers and health care providers interfaceto access patient's data and e-counseling platform. The system comprisesa secure communication network for receiving a transfer of data from/todevices, data servers through secure communication protocol. The systemincludes built-in user voting system for every single feature that feedssystem self-optimizing engine. The system gives patient access to“DISTROY” button, which enables patients to destroy all his/her datacontribution to PCH ECO system indefinitely.

FIG. 20 has extensive description of the system, from overall view, asan example. For example, patient records 2001 include clinical data,genetic data, environment/climate data, food and medication intake data,public record/civil/criminal data, personal life style, behavioral data,financial data, work, education, or the like-data, wearable bio-sensor,EKG, brain wave, body area network-data, direct or indirect patientfeedback data, caregivers' feedback data, or the like. The records arecommunicated to outside through communication layer 2002 and 2003, whichconnects to population health database 2011, through 2002, communicationlayer, as well as machine learning engine 1706, and precision behavioraland clinical intervention engine 2004, which interacts with machinelearning engine 2004. These are also connected to PerSoN Clinic withpatient interface 2012, which connects to the user 2010, which in turnare both connected to the point of care touch 2008, which is alsoconnected to patient records 2001, through connecters 2002 and 2006.Point of care touch at 2007 is also connected to EMR/HER system 2009,which is the hardware that installed in, for example, a doctor's officefor the user/patient to interact/interface with for her owndata/info/input, and the like.

FIG. 21 is used to illustrate features and components of the PCHECO-system. In FIG. 21 , the components of the PerSoN Clinic andinteractions with other subcomponents/subsystems, in theenvironment/platform are shown. Such features include the patient beingin control, with sensors collecting, wearable's, lifestyle activities,patient-initiated feedback, public forum data feed, machine learningengine, intervention engine, and personalized treatment, as an example.The direct feedback can be provided, for example, from the patientinputting survey or data into system, and the indirect data the comesfrom pin data and wearables, and the like. Feedback can be in real time,which helps the system to compare the patient with similar class orindividuals for diagnosis and plan for the patient, for example, byanalyzing life style and social behavior, among spectrum of factors,parameters, and people, for example, to analyze depression orprobability of such event, and the like.

In one example, the doctor does not have to know the criminal records toexplain or predict the environmental effects on a patient in terms ofstress causing factors, and it remains private, and the machine canstill do the job of the prediction and diagnosis. The Point of caretouch hardware, that installed at various locations for the users, canhave biometrics or unique ID/password hardware at doctor's office, forconfidentiality and privacy issues. With the PerSoN Clinic hardware, thepatient controls system and its input/output, in one example, so that nodoctor or no insurance can break that control, for the privacy. Thesystem provides all the suitable tools that the patient can employ tocontrol the data and system, and the like.

The system can be employed for chronic problems, pain problems,addiction, psychological problems, clinical interventions,relationships, pain management, for pain duration, and the like. Thesmart pins (e.g., event driven) can be employed for recording the eventsand inputting the data into system, for analysis, and the like. With thesmart pin a person can use the pin for communication, and can beconjured as a tag, and the like, employ Bluetooth or RFID or WiFitechnologies for communication, or by any other suitable communicationprotocols available, wirelessly or wired/other methods, and the like.Such PerSoN's NFC enabled bio sensors and NFC pins can be used in/onvarious positions or items. The tags or pins can be passive or active,and they can connect to the mobile application, smart watch, smartphone, or mobile devices, such as smart key chain, and the like.

Such biosensors can measure many body functions or hormones orbiological effects, for example, sweat, for stress level measurement,and the like. For example, once somebody is nervous or stressed, theycan tap the sensor on their wearable device to measure the sweat, andthus, stress level, to give more objective data, versus more subjectivemood or feeling from the user herself, to confirm or analyze thepsychology and clinical state of a person, from various angles andthrough various lenses, with various metrics and thresholds, for morecomplete view of the situation to predict better to avoid disasters ordamages, both lives and properties. Such analysis may also include be acombination of both mental and physical effects in play at a given time,in addition to context and environment around the person.

The real-time communication, such as with WiFi technology, isadvantageous for real-time measurements, for analysis of the totality ofthe situation. For example, with pins at/on mother's dress/body, as wellas the infant's, one can monitor when and how long the baby was pickedup or held by mother or baby sitter, or violent shaking by an improperbaby sitter can be recorded (and e.g., with an alarm sent to suitablepeople), to prevent damages and monitor the health of a baby, as well asother studies to diagnose the problems with babies, for example, throughbig data analysis, and the like. Such features can also be used tocorrelate with the bonding of baby with mother, with correspondinghealth consequences, and the like.

A server, or smart device, or smart watch, or central device ordistributed farm, or any combination of the above can be employed, withvarious computing devices for analysis by the platform, with userinterfaces and tools for the user or patient to control and getinformation and analysis, for the best results for prevention and cure,supported by the research of the professionals, to coordinate theanalysis for medical diagnosis and cure or prevention, and the like.

The patient interface and devices can be configured to communicate witha human through one or multiple ways of human senses (e.g., sight,hearing, smell, taste and touch) and collect human data, and humanfeedback through one or multiple ways of human senses (e.g., sight,hearing, smell, taste and touch).

The PCH ECO-system patient interface can include voice enabled mobileinterface and devices. The PCH ECO device is voice enabled system thatcomes in different shapes, e.g., doll, tower and/or toy pet that can bepaired with pin device. The patient can pick a name for its PCH ECOdevice and communicate with the device by calling its name or touchingit for pre-defined functions. The patient can report his/herhealth-related feedback through voice and touch. Such PCH ECO device caninclude a facial recognition module, biosensors, EKG sensor, CO2 andchemical detection sensors, noise, smell and motion detector sensors,and the like.

FIG. 22 is used to illustrate a high-level data flow for a populating apopulation health system of the PCH KO-system. In FIG. 22 , anaggregated Population Health database 2011 within PCH ECO-systemdatabase layer is provided with patient data, for example, includingclinical, genetic, life style, financial, social, civil and criminalrecords, and the like, 2201. A di-identification and language processingengine 2202 processes patient data as per HIPAA and GPRD regulations andtranslates none English patient records to English and serve as freetext analyzing and processing engine. The PCH ECO-system can beconnected through open and available relevant third-party health API toaggregate patient related data at 2205. The PCH ECO-system service layeralso provides access to collection of PCH ECO-system API 2201 thatenables researchers access to di-identified patient's health dataindexed with different identifiers and or collect data from public andprivate relevant data APIs.

The Patient controlled health eco-system, distributed communicationprotocol within PCH ECO-system facilitates secure communication and datatransfer with internal and external modules. PCH ECO ApplicationProgramming Interfaces (API) facilitate open communication with externalsystem for sharing patient information with patient selected andapproved, Electronic Medical Record. Research institutes can access PCHECO di-identified data layer through designated API.

FIG. 23 is used to illustrate a high-level logical flow of sub-systemsinteractions within the PCH ECO-system. In FIG. 23 , the system collectsimplicit (step 2303) and explicit (steps 2302 and 2301) patient's dataand aggregating such data (step 2304), for identifying the behavioraland clinical trends (step 2305) within every dataset for single orcombine personal identifiers. Employed are fuzzy logic and/or neuralnetwork combinations for the collected data to analyze the system model,to obtain index value for every personal identifiers which then will beinput to our Artificial Intelligent engine with proprietary method toidentify relevant intervention in recommended form (step 2311).

FIG. 24 is used to illustrate a high-level design system modules andengines of the PCH ECO-system and method. In FIG. 24 , the Patientcontrolled health eco-system, proprietary Machine Learning Engine 1706and its built-in Artificial Intelligent algorithm are trained by anysuitable self-optimizing methods at 2402, 2403, 2404, 2405, 2406, 2407,and 2408. The PCH ECO self-optimizing methods and modules interact withand feed to Active Data modeling system 2408, Precision behavioral andclinical intervention engine 2004, Data Analysis modules at 2402, 2403,2404, 2405, and 2409. The PCH ECO System Active Data modeling engine2408, for example, utilizes machine learning engine (MLE) 1706, todefine and redefine fuzzy sets 2407 and create active fuzzy relationaldatabase to objectively measure personal feedback for providingpersonalized clinical and behavioral intervention at 2410, just in-timethrough mobile system and/or wearable and other devices

The Patient controlled health eco-system, provides private and publicsocial networking, disease management modules, virtual support andVirtual Charity support. While such module provides essential supportfor patient however, they also create wealth of implicit data regardingpatient's behavior which can be used for creating more effectiveintervention. The disease management modules are designed based onlatest scientific best practices with option for care providers tomonitor patient's progress and provide intervention and feedback. Thedisease specific self-help health management modules, for example,including major epidemic diseases, smoking cessation and depressionmanagement with built-in user rating mechanism for every features thatprovide system admin with aggregated user feedback for futureadvancement of the system. The patient initiated private socialnetworking (Patient Private Wall—PPW) is private virtual environmentthat a patient's invitee can have access to. The PPW is virtualenvironment that patient can have full access to. Patients can deleteand destroy all the communication within that wall permanently from PCHECO-system. The virtual community support component connects patientsand caregivers with common interest and/or disease condition withintheir selected geographical distance. This feature enables patientwithin a community or neighborhood to connect and support each other.They have access to common communication features, such as one-one andgroup communication and multi-media media sharing. For example, thecommunity can have access to a feature call “Remedy,” every conversationcan be marked as “Remedy” and voted by viewers. The “Remedy” is piece ofconversation that includes health, wellness and/or lifestyle tip. Everyconversation that is marked as “remedy” is searchable and can be viewedand rated by every member of PCH ECO-system and can be translated todifferent languages.

The PCH ECO Virtual Charity support connects patients and care giverswith particular needs (e.g., financial and/or otherwise) to supportgroups, individuals or charity organizations capable of supporting thepatient with the needs. The Patient controlled health eco-system, voiceenable interactive communication is integrated into PCH ECO-systemutilizes third party voice recognition technologies and optimize byproprietary PCH ECO machine learning engine at 2301.

The Patient controlled health eco-system provides researchers and healthcare providers interface to access patient's data in real time ande-counseling platform to connect with patients within their network asneeded. Patients can define access level for multiple and each careprovider. This enables a patient to be in full control of their healthrecord data. Care providers and researchers can define the communicationguidelines and venue (e.g., Online messaging, Audio or Video with in 8am to 6 pm, only online messaging).

The Patient controlled health eco-system, includes a securecommunication network for receiving and transfer of data from/todevices, data servers through secure communication protocol HTTPS, usingTransport Layer Security (TLS). When PCH ECO devices communicate throughWiFi the WPA2+AES security protocol will be used. The systemself-optimizing engine provides usability report on every PCH ECOfeatures by aggregating user rating data for each feature and thefeature's traffic data. The system gives patient access to “DESTROY”button, which enables patients to destroy all his/her data contributionto PCH ECO system indefinitely. The PCH ECO system is fully compliancewith HIPPA and GPRD privacy and security guidelines. In furtherillustrative embodiments, any suitable variations of the above teachingare also intended to be covered by this patent application, as will beappreciated by those of ordinary skill in the relevant art(s).

The above-described devices and subsystems of the illustrativeembodiments can include, for example, any suitable servers,workstations, PCs, laptop computers, PDAs, Internet appliances, handhelddevices, cellular telephones, wireless devices, other devices, and thelike, capable of performing the processes of the illustrativeembodiments. The devices and subsystems of the illustrative embodimentscan communicate with each other using any suitable protocol and can beimplemented using one or more programmed computer systems or devices.

One or more interface mechanisms can be used with the illustrativeembodiments, including, for example, Internet access, telecommunicationsin any suitable form (e.g., voice, modem, and the like), wirelesscommunications media, and the like. For example, employed communicationsnetworks or links can include one or more wireless communicationsnetworks, cellular communications networks, 5G communications networks,Public Switched Telephone Network (PSTNs), Packet Data Networks (PDNs),the Internet, intranets, a combination thereof, and the like.

It is to be understood that the devices and subsystems of theillustrative embodiments are for illustrative purposes, as manyvariations of the specific hardware used to implement the illustrativeembodiments are possible, as will be appreciated by those skilled in therelevant art(s). For example, the functionality of one or more of thedevices and subsystems of the illustrative embodiments can beimplemented via one or more programmed computer systems or devices.

To implement such variations as well as other variations, a singlecomputer system can be programmed to perform the special purposefunctions of one or more of the devices and subsystems of theillustrative embodiments. On the other hand, two or more programmedcomputer systems or devices can be substituted for any one of thedevices and subsystems of the illustrative embodiments. Accordingly,principles and advantages of distributed processing, such as redundancy,replication, and the like, also can be implemented, as desired, toincrease the robustness and performance of the devices and subsystems ofthe illustrative embodiments.

The devices and subsystems of the illustrative embodiments can storeinformation relating to various processes described herein. Thisinformation can be stored in one or more memories, such as a hard disk,optical disk, magneto-optical disk, RAM, and the like, of the devicesand subsystems of the illustrative embodiments. One or more databases ofthe devices and subsystems of the illustrative embodiments can store theinformation used to implement the illustrative embodiments of thepresent inventions. The databases can be organized using data structures(e.g., records, tables, arrays, fields, graphs, trees, lists, and thelike) included in one or more memories or storage devices listed herein.The processes described with respect to the illustrative embodiments caninclude appropriate data structures for storing data collected and/orgenerated by the processes of the devices and subsystems of theillustrative embodiments in one or more databases thereof.

All or a portion of the devices and subsystems of the illustrativeembodiments can be conveniently implemented using one or more generalpurpose computer systems, microprocessors, digital signal processors,micro-controllers, and the like, programmed according to the teachingsof the illustrative embodiments of the present inventions, as will beappreciated by those skilled in the computer and software arts.Appropriate software can be readily prepared by programmers of ordinaryskill based on the teachings of the illustrative embodiments, as will beappreciated by those skilled in the software art. Further, the devicesand subsystems of the illustrative embodiments can be implemented on theWorld Wide Web. In addition, the devices and subsystems of theillustrative embodiments can be implemented by the preparation ofapplication-specific integrated circuits or by interconnecting anappropriate network of conventional component circuits, as will beappreciated by those skilled in the electrical art(s). Thus, theillustrative embodiments are not limited to any specific combination ofhardware circuitry and/or software.

Stored on any one or on a combination of computer readable media, theillustrative embodiments of the present inventions can include softwarefor controlling the devices and subsystems of the illustrativeembodiments, for driving the devices and subsystems of the illustrativeembodiments, for enabling the devices and subsystems of the illustrativeembodiments to interact with a human user, and the like. Such softwarecan include, but is not limited to, device drivers, firmware, operatingsystems, development tools, applications software, and the like. Suchcomputer readable media further can include the computer program productof an embodiment of the present inventions for performing all or aportion (if processing is distributed) of the processing performed inimplementing the inventions. Computer code devices of the illustrativeembodiments of the present inventions can include any suitableinterpretable or executable code mechanism, including but not limited toscripts, interpretable programs, dynamic link libraries (DLLs), Javaclasses. Moreover, parts of the processing of the illustrativeembodiments of the present inventions can be distributed for betterperformance, reliability, cost, and the like.

As stated above, the devices and subsystems of the illustrativeembodiments can include computer readable medium or memories for holdinginstructions programmed according to the teachings of the presentinventions and for holding data structures, tables, records, and/orother data described herein. Computer readable medium can include anysuitable medium that participates in providing instructions to aprocessor for execution. Such a medium can take many forms, includingbut not limited to, non-volatile media, volatile media, transmissionmedia, and the like. Non-volatile media can include, for example,optical or magnetic disks, magneto-optical disks, and the like. Volatilemedia can include dynamic memories, and the like. Transmission media caninclude coaxial cables, copper wire, fiber optics, and the like.Transmission media also can take the form of acoustic, optical,electromagnetic waves, and the like, such as those generated duringradio frequency (RF) communications, infrared (IR) data communications,and the like.

While the present invention has been described in connection with anumber of embodiments and implementations, the present invention is notso limited but rather covers various modifications and equivalentarrangements, which will fall within the purview of the appended claims.

What is claimed is:
 1. A computer implemented system for a medicalplatform for use with at least one user in accordance with treatment fora patient, the system comprising: a database configured to receiveimplicit and explicit patient information and generate aggregatedpatient information; a wearable device configured to collect and sendthe implicit and explicit patient information to the database, thewearable device including: an interface configured to receive implicitpatient information on subjective factors including at least one ofpain, user behavior, demographic and medical background from theaggregate information from the database; at least one near-fieldcommunication sensor and biosensor, the near-field communication sensorand biosensor being configured to measure health condition factors ofthe user and record data of the communication between the patient andthe users, wherein the measured health condition factors of the usersare included in the explicit patient information; a machine learningsystem configured to: receive the aggregated patient information fromthe database, identify sentiment of the patient and the user based onthe recorded data of the communication between the patient and the user;and generate and transmit to the user a recommendation related totreatment based on the identified sentiment and the aggregated patientinformation, and a user interface display configured to display thegenerated recommendation to the user.
 2. The system of claim 1, furthercomprising a wearable device configured to receive the explicit andimplicit patient information and the data from the communication betweenthe patient and the user.
 3. The system of claim 2, wherein the wearabledevice transmits the patient information to the database to aggregateavailable patient information.
 4. The system of claim 1, wherein theuser is a healthcare professional engaged in treating the patient, andwherein the aggregated patient information from the database is receivedby the machine learning system and the recorded data of thecommunication between the patient and the user.
 5. The system of claim4, wherein the user is a supporting member of the patient, and whereinthe aggregated patient information from the database is received by themachine learning system and the recorded data of the communicationbetween the patient and the user.
 6. The system of claim 5, wherein themachine learning system determines the sentiment of the patient and theuser based on the communication via the aggregated patient database. 7.The system of claim 1, wherein the user is a healthcare professionalengaged in treating the patient, and wherein the step of generating arecommendation to the user based on the identified sentiment is repeatedafter each single communication between the patient and the user.
 8. Thesystem of claim 7, the user is a supporting member of the patient, andwherein the step of generating a recommendation to the user based on theidentified sentiment is repeated after each single communication betweenthe patient and the user.
 9. The system of claim 8, wherein the step ofidentifying sentiment of the patient and the user based on the recordeddata of the communication between the patient and the user, furtherincludes identifying sentiment from recorded text-based communicationbetween the patient and the user.
 10. The system of claim 9, wherein thestep of identifying sentiment of the patient and the user based on therecorded data of the communication between the patient and the user,further includes identifying bilateral sentiment of both the patient andthe user.
 11. The system of claim 10, wherein the step of generating arecommendation to the user based on the identified bilateral sentiment,further includes recommending at least one of diction, tone, emoji andpunctuation to manage the patient's sentiment.
 12. The system of claim1, wherein the user interface display is configured to alert the user ofchanges in the bilateral sentiment of the recorded communication betweenthe user and the patient.
 13. The system of claim 11, wherein the userinterface display is configured to collect feedback from the user andthe patient to track the effect of the recommendation generated by themachine learning system.
 14. The system of claim 13, wherein the machinelearning system includes an artificial intelligence (AI) engineconfigured to train based on the feedback collected by the userinterface display of the users and the patient.
 15. The system of claim1, wherein the machine learning system includes an artificialintelligence (AI) engine configured to predict the overall sentiment ofthe recorded communication between the user and the patient based on theaggregated patient information.
 16. The system of claim 15, wherein themachine learning system includes an artificial intelligence (AI) engineconfigured to estimate the effectiveness level of the generatedrecommendation.
 17. The system of claim 1, wherein the machine learningsystem is configured to perform the identify and generate steps formultiple users.